Entropy Application for Forecasting
This book shows the potential of entropy and information theory in forecasting, including both theoretical developments and empirical applications. The contents cover a great diversity of topics, such as the aggregation and combination of individual forecasts, the comparison of forecasting performan...
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| Format: | Online |
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| Langue: | anglais |
| Publié: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Sujets: | |
| Accès en ligne: | ONIX_20210501_9783039364879_629 |
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| _version_ | 1869527092858716160 |
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| collection | Directory of Open Access Books |
| description | This book shows the potential of entropy and information theory in forecasting, including both theoretical developments and empirical applications. The contents cover a great diversity of topics, such as the aggregation and combination of individual forecasts, the comparison of forecasting performance, and the debate concerning the tradeoff between complexity and accuracy. Analyses of forecasting uncertainty, robustness, and inconsistency are also included, as are proposals for new forecasting approaches. The proposed methods encompass a variety of time series techniques (e.g., ARIMA, VAR, state space models) as well as econometric methods and machine learning algorithms. The empirical contents include both simulated experiments and real-world applications focusing on GDP, M4-Competition series, confidence and industrial trend surveys, and stock exchange composite indices, among others. In summary, this collection provides an engaging insight into entropy applications for forecasting, offering an interesting overview of the current situation and suggesting possibilities for further research in this field. |
| format | Online |
| id | doab-20.500.12854ir-68883 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-688832024-03-29T19:31:06Z Entropy Application for Forecasting Lopez-Menendez, Ana Jesus Pérez-Suárez, Rigoberto thema EDItEUR::K Economics, Finance, Business and Management This book shows the potential of entropy and information theory in forecasting, including both theoretical developments and empirical applications. The contents cover a great diversity of topics, such as the aggregation and combination of individual forecasts, the comparison of forecasting performance, and the debate concerning the tradeoff between complexity and accuracy. Analyses of forecasting uncertainty, robustness, and inconsistency are also included, as are proposals for new forecasting approaches. The proposed methods encompass a variety of time series techniques (e.g., ARIMA, VAR, state space models) as well as econometric methods and machine learning algorithms. The empirical contents include both simulated experiments and real-world applications focusing on GDP, M4-Competition series, confidence and industrial trend surveys, and stock exchange composite indices, among others. In summary, this collection provides an engaging insight into entropy applications for forecasting, offering an interesting overview of the current situation and suggesting possibilities for further research in this field. 2021-05-01T15:32:00Z 2021-05-01T15:32:00Z 2020 book ONIX_20210501_9783039364879_629 9783039364879 9783039364886 https://directory.doabooks.org/handle/20.500.12854/68883 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/2650 https://mdpi.com/books/pdfview/book/2650 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03936-488-6 10.3390/books978-3-03936-488-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039364879 9783039364886 200 Basel, Switzerland open access |
| spellingShingle | thema EDItEUR::K Economics, Finance, Business and Management Entropy Application for Forecasting |
| title | Entropy Application for Forecasting |
| title_full | Entropy Application for Forecasting |
| title_fullStr | Entropy Application for Forecasting |
| title_full_unstemmed | Entropy Application for Forecasting |
| title_short | Entropy Application for Forecasting |
| title_sort | entropy application for forecasting |
| topic | thema EDItEUR::K Economics, Finance, Business and Management |
| topic_facet | thema EDItEUR::K Economics, Finance, Business and Management |
| url | ONIX_20210501_9783039364879_629 |